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Cancers
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Brain Cancer: Imaging and Radiotherapy
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Brain Cancer: Imaging and Radiotherapy

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Therapy".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 6429

Special Issue Editor

Dr. Brigitta G. Baumert

E-Mail Website
Guest Editor
Institute of Radiation Oncology, Cantonal Hospital Graubuenden, 7000 Chur, Switzerland
Interests: neuro-oncology; radiation-oncology; brain tumours; imaging for radiotherapy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The aim of this Special Issue, “Brain Cancer: Imaging and Radiotherapy”, is to present the challenges of imaging brain tumours and its impact on radiation and treatment monitoring. Imaging plays a major role in radiation therapy. It is used for the definition of radiation treatment volumes such as the definition of the tumor, normal tissues, treatment planning (e.g., image-guided radiotherapy), treatment monitoring, and follow-up.

All aspects of imaging for glioma, meningioma, and radiomics, specifically in its use for radiation therapy, are welcome. Original papers are preferable. Novel aspects such as radiomics (e.g., for dose painting) or the use and possible integration of artificial intelligence for radiation treatment planning as well as treatment monitoring such as daily imaging with cone beam CTs are topics of interest for this Special Issue. 

Dr. Brigitta G. Baumert
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • brain cancer and radiotherapy
  • radiation treatment
  • cone beam CT
  • PTV
  • follow-up
  • image guide radiotherapy

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Published Papers (3 papers)

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Research

26 pages, 5323 KiB  
Article
Evaluating Physiological MRI Parameters in Patients with Brain Metastases Undergoing Stereotactic Radiosurgery—A Preliminary Analysis and Case Report
by Eva E. van Grinsven, Jordi de Leeuw, Jeroen C. W. Siero, Joost J. C. Verhoeff, Martine J. E. van Zandvoort, Junghun Cho, Marielle E. P. Philippens and Alex A. Bhogal
Cancers 2023, 15(17), 4298; https://doi.org/10.3390/cancers15174298 - 28 Aug 2023
Cited by 2 | Viewed by 1567
Abstract
Brain metastases occur in ten to thirty percent of the adult cancer population. Treatment consists of different (palliative) options, including stereotactic radiosurgery (SRS). Sensitive MRI biomarkers are needed to better understand radiotherapy-related effects on cerebral physiology and the subsequent effects on neurocognitive functioning. [...] Read more.
Brain metastases occur in ten to thirty percent of the adult cancer population. Treatment consists of different (palliative) options, including stereotactic radiosurgery (SRS). Sensitive MRI biomarkers are needed to better understand radiotherapy-related effects on cerebral physiology and the subsequent effects on neurocognitive functioning. In the current study, we used physiological imaging techniques to assess cerebral blood flow (CBF), oxygen extraction fraction (OEF), cerebral metabolic rate of oxygen (CMRO2) and cerebrovascular reactivity (CVR) before and three months after SRS in nine patients with brain metastases. The results showed improvement in OEF, CBF and CMRO2 within brain tissue that recovered from edema (all p ≤ 0.04), while CVR remained impacted. We observed a global post-radiotherapy increase in CBF in healthy-appearing brain tissue (p = 0.02). A repeated measures correlation analysis showed larger reductions within regions exposed to higher radiotherapy doses in CBF (rrm = −0.286, p < 0.001), CMRO2 (rrm = −0.254, p < 0.001), and CVR (rrm = −0.346, p < 0.001), but not in OEF (rrm = −0.004, p = 0.954). Case analyses illustrated the impact of brain metastases progression on the post-radiotherapy changes in both physiological MRI measures and cognitive performance. Our preliminary findings suggest no radiotherapy effects on physiological parameters occurred in healthy-appearing brain tissue within 3-months post-radiotherapy. Nevertheless, as radiotherapy can have late side effects, larger patient samples allowing meaningful grouping of patients and longer follow-ups are needed. Full article
(This article belongs to the Special Issue Brain Cancer: Imaging and Radiotherapy)
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11 pages, 1865 KiB  
Article
Impact of Postoperative Changes in Brain Anatomy on Target Volume Delineation for High-Grade Glioma
by Cas Stefaan Dejonckheere, Anja Thelen, Birgit Simon, Susanne Greschus, Mümtaz Ali Köksal, Leonard Christopher Schmeel, Timo Wilhelm-Buchstab and Christina Leitzen
Cancers 2023, 15(10), 2840; https://doi.org/10.3390/cancers15102840 - 19 May 2023
Cited by 1 | Viewed by 2034
Abstract
High-grade glioma has a poor prognosis, and radiation therapy plays a crucial role in its management. Every step of treatment planning should thus be optimised to maximise survival chances and minimise radiation-induced toxicity. Here, we compare structures needed for target volume delineation between [...] Read more.
High-grade glioma has a poor prognosis, and radiation therapy plays a crucial role in its management. Every step of treatment planning should thus be optimised to maximise survival chances and minimise radiation-induced toxicity. Here, we compare structures needed for target volume delineation between an immediate postoperative magnetic resonance imaging (MRI) and a radiation treatment planning MRI to establish the need for the latter. Twenty-eight patients were included, with a median interval between MRIs (range) of 19.5 (8–50) days. There was a mean change in resection cavity position (range) of 3.04 ± 3.90 (0–22.1) mm, with greater positional changes in skull-distant (>25 mm) resection cavity borders when compared to skull-near (≤25 mm) counterparts (p < 0.001). The mean differences in resection cavity and surrounding oedema and FLAIR hyperintensity volumes were −32.0 ± 29.6% and −38.0 ± 25.0%, respectively, whereas the mean difference in midline shift (range) was −2.64 ± 2.73 (0–11) mm. These data indicate marked short-term volumetric changes and support the role of an MRI to aid in target volume delineation as close to radiation treatment start as possible. Planning adapted to the actual anatomy at the time of radiation limits the risk of geographic miss and might thus improve outcomes in patients undergoing adjuvant radiation for high-grade glioma. Full article
(This article belongs to the Special Issue Brain Cancer: Imaging and Radiotherapy)
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16 pages, 694 KiB  
Article
MRI-Based Deep Learning Tools for MGMT Promoter Methylation Detection: A Thorough Evaluation
by Lucas Robinet, Aurore Siegfried, Margaux Roques, Ahmad Berjaoui and Elizabeth Cohen-Jonathan Moyal
Cancers 2023, 15(8), 2253; https://doi.org/10.3390/cancers15082253 - 12 Apr 2023
Cited by 3 | Viewed by 2173
Abstract
Glioblastoma is the most aggressive primary brain tumor, which almost systematically relapses despite surgery (when possible) followed by radio-chemotherapy temozolomide-based treatment. Upon relapse, one option for treatment is another chemotherapy, lomustine. The efficacy of these chemotherapy regimens depends on the methylation of a [...] Read more.
Glioblastoma is the most aggressive primary brain tumor, which almost systematically relapses despite surgery (when possible) followed by radio-chemotherapy temozolomide-based treatment. Upon relapse, one option for treatment is another chemotherapy, lomustine. The efficacy of these chemotherapy regimens depends on the methylation of a specific gene promoter known as MGMT, which is the main prognosis factor for glioblastoma. Knowing this biomarker is a key issue for the clinician to personalize and adapt treatment to the patient at primary diagnosis for elderly patients, in particular, and also upon relapse. The association between MRI-derived information and the prediction of MGMT promoter status has been discussed in many studies, and some, more recently, have proposed the use of deep learning algorithms on multimodal scans to extract this information, but they have failed to reach a consensus. Therefore, in this work, beyond the classical performance figures usually displayed, we seek to compute confidence scores to see if a clinical application of such methods can be seriously considered. The systematic approach carried out, using different input configurations and algorithms as well as the exact methylation percentage, led to the following conclusion: current deep learning methods are unable to determine MGMT promoter methylation from MRI data. Full article
(This article belongs to the Special Issue Brain Cancer: Imaging and Radiotherapy)
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